MOL signs technology consulting agreement with Yokohama National University professor

On 30 August, Mitsui O.S.K. Lines, Ltd. (MOL; President & CEO: Junichiro Ikeda) announced that the company has concluded a technology consulting agreement with Professor Tomoharu Nagao1 of the Yokohama National University (Headquarters: Yokohama, Kanagawa Pref.; President: Yuichi Hasebe) Graduate School of Environment and Information Sciences, who is the creator of the next-generation AI advanced machine learning2 and the percolative learning method3.

The MOL Group has worked with Professor Nagao since 2016 to forecast the dry bulk market by analysing data related to economic issues and maritime affairs. It will continue to promote the use and application of ICT-based trends in advanced digitalisation by concluding this technology consulting agreement and holding regular advisory meetings and internal review meetings.

MOL aims to become a ‘corporate group of competitive number one businesses’, under the ‘Vision for the MOL Group 10 years from now’ set out in the ‘Rolling Plan 2018’ management plan by enhancing its services through the use and application of ICT.

1. Tomoharu Nagao is a leading authority on advanced machine leaning, and has pioneered many unique advanced calculation models by applying advanced calculation methods to image processing and recognition, nerve circuit networks, time-series forecast, and so on. He is current position since 2001 after serving as an assistant professor in the Graduate school of Tokyo Institute of Technology. His work focuses on industry-academia cooperation, drawing upon his strong track record of joint studies with many companies. He also serves as CTO of a venture of the university.

2. Advanced machine learning is said to be the next stage of artificial intelligence after deep learning, which realises autonomous solution of problems.

3. The percolative learning method is a model that ‘percolates’ future information available only during learning into information, which can be used even during practical use. It is expected to allow much higher accuracy in forecasting future changes (Yokohama National University: Nagao Lab: Patent Number 2017-153613).